The Stanford Medicine data science ecosystem for clinical and translational research

Objective To describe the infrastructure, tools, and services developed at Stanford Medicine to maintain its data science ecosystem and research patient data repository for clinical and translational research. Materials and Methods The data science ecosystem, dubbed the Stanford Data Science Resources (SDSR), includes infrastructure and tools to create, search, retrieve, and analyze patient data, as well as services for data deidentification, linkage, and processing to extract high-value information from healthcare IT systems. Data are made available via self-service and concierge access, on HIPAA compliant secure computing infrastructure supported by in-depth user training. Results The Stanford Medicine Research Data Repository (STARR) functions as the SDSR data integration point, and includes electronic medical records, clinical images, text, bedside monitoring data and HL7 messages. SDSR tools include tools for electronic phenotyping, cohort building, and a search engine for patient timelines. The SDSR supports patient data collection, reproducible research, and teaching using healthcare data, and facilitates industry collaborations and large-scale observational studies. Discussion Research patient data repositories and their underlying data science infrastructure are essential to realizing a learning health system and advancing the mission of academic medical centers. Challenges to maintaining the SDSR include ensuring sufficient financial support while providing researchers and clinicians with maximal access to data and digital infrastructure, balancing tool development with user training, and supporting the diverse needs of users. Conclusion Our experience maintaining the SDSR offers a case study for academic medical centers developing data science and research informatics infrastructure. Lay Summary Research patient data repositories are essential for health systems to learn from the experiences of their patients and for advancing the mission of academic medical centers. In this paper, we describe methods, tools, and practices at Stanford Medicine to maintain its research patient data repository and computing resources to support clinical and translational research, which together comprise the Stanford Medicine Data Science Resources (SDSR). The SDSR includes computing infrastructure and tools to create, search, retrieve, and analyze patient data. Data are made available via self-service and staff supported access, on secure computers. The Stanford Medicine Research Data Repository functions as the SDSR data integration point, and includes patient records such as clinical images, text, bedside monitoring data and administrative records. SDSR tools include a search engine for patient data and data analysis tools for identifying and retrieving data about groups of patients with shared characteristics, such as a diagnosis or treatment. The SDSR also supports patient data collection, reproducible research, and teaching using healthcare data, and facilitates industry collaborations and observational studies. Challenges to maintaining the SDSR include ensuring sufficient financial support while providing researchers and clinicians with maximal access to data and digital infrastructure, balancing tool development with user training, and supporting the diverse needs of users.